Perceptual learning: stimulus-specific learning from low-level visual plasticity?

A new study has found that changes in visual cortical processing account for behavioral perceptual learning, supporting the idea that stimulus-specific learning can result from low-level visual plasticity.     

Cortical plasticity: Is it time for a change?

Classical studies of plasticity in the visual cortex have been interpreted in terms of heterosynaptic competition between inputs. But an alternative type of 'homosynaptic' plasticity can explain many recent observations and has recently received experimental support. Perhaps both types of plasticity are important.     

Epidermal homeostasis: do committed progenitors work while stem cells sleep?

Tracking the fate of cells in murine epidermis in vivo has revealed that a committed progenitor cell population can maintain normal adult tissue in the long term without support from a long-lived, self-renewing population of stem cells. Here, we argue that these results challenge the dogma that stem-cell proliferation is required for the cellular homeostasis of the epidermis and other adult tissues, with important implications for tissue physiology and disease.     

Perceptual learning and sensomotor flexibility: cortical plasticity under attentional control?

Recent research reveals long-lasting cortical plasticity of early sensory cortices even in adults. Sensory signals could be modified under top-down control if necessary quite early in order to optimize their signal-to-noise ratio, leading to 'low level' or 'early' perceptual learning (PL). For easy tasks, such elaborate top-down influences are usually not required, and learning is restricted to late selection of the appropriate signals on higher cortical levels, which seems easier and faster to achieve. But to reach the absolute limits of sensory performance, PL seems to optimize the entire chain of sensory processing. Hence, improvement for these extreme perceptual abilities is quite specific for a number of stimulus parameters, such as the position in the visual field and sometimes even the trained eye, reflecting the specificity of receptive fields in early sensory cortices. Early PL may be just one example--even if a very extensive one--of the mechanisms of neuronal plasticity and sensomotor flexibility that are constantly updating our sensomotor representations as a result of experience. As an illustration, this review contains some new experimental results on PL and sensory flexibility in the context of adaptation to multifocal intraocular lenses.     

Hippocampal synaptic plasticity: role in spatial learning or the automatic recording of attended experience?

Allocentric spatial learning can sometimes occur in one trial. The incorporation of information into a spatial representation may, therefore, obey a one-trial correlational learning rule rather than a multi-trial error-correcting rule. It has been suggested that physiological implementation of such a rule could be mediated by N-methyl-D-aspartate (NMDA) receptor-dependent long-term potentiation (LTP) in the hippocampus, as its induction obeys a correlational type of synaptic learning rule. Support for this idea came originally from the finding that intracerebral infusion of the NMDA antagonist AP5 impairs spatial learning, but studies summarized in the first part of this paper have called it into question. First, rats previously given experience of spatial learning in a watermaze can learn a new spatial reference memory task at a normal rate despite an appreciable NMDA receptor blockade. Second, the classical phenomenon of ''blocking'' occurs in spatial learning. The latter finding implies that spatial learning can also be sensitive to an animal''s expectations about reward and so depend on more than the detection of simple spatial correlations. In this paper a new hypothesis is proposed about the function of hippocampal LTP. This hypothesis retains the idea that LTP subserves rapid one-trial memory, but abandons the notion that it serves any specific role in the geometric aspects of spatial learning. It is suggested that LTP participates in the automatic recording of attended experience'': a subsystem of episodic memory in which events are temporarily remembered in association with the contexts in which they occur. An automatic correlational form of synaptic plasticity is ideally suited to the online registration of context event associations. In support, it is reported that the ability of rats to remember the most recent place they have visited in a familiar environment is exquisitely sensitive to AP5 in a delay-dependent manner. Moreover, new studies of the lasting persistence of NMDA-dependent LTP, known to require protein synthesis, point to intracellular mechanisms that enable transient synaptic changes to be stabilized if they occur in close temporal proximity to important events. This new property of hippocampal LTP is a desirable characteristic of an event memory system.     

Cortical maps: a role for astrocytes?

Astrocytes are a multifunctional cell type in the nervous system that can influence neurons and synapses in numerous ways. Astrocytes have been suggested to play important roles in synapse formation during development, as well as in multiple forms of synaptic plasticity in the developing and adult brain. Astrocytes respond to nearby neural activity with elevations in cytosolic calcium concentration, and in sensory cortex these calcium responses have been shown to be topographically aligned to neuronal sensory maps. Here, we review recent evidence for astrocyte interactions with neural circuits, with particular emphasis on how these interactions may shape the development, arrangement and plasticity of cortical sensory maps.     

Cross-modal plasticity: where and how?

Animal studies have shown that sensory deprivation in one modality can have striking effects on the development of the remaining modalities. Although recent studies of deaf and blind humans have also provided convincing behavioural, electrophysiological and neuroimaging evidence of increased capabilities and altered organization of spared modalities, there is still much debate about the identity of the brain systems that are changed and the mechanisms that mediate these changes. Plastic changes across brain systems and related behaviours vary as a function of the timing and the nature of changes in experience. This specificity must be understood in the context of differences in the maturation rates and timing of the associated critical periods, differences in patterns of transiently existing connections, and differences in molecular factors across brain systems.     

Why sleep?

All living organisms show a regular, daily period of reduced activity. But to what extent could this be sleep, and what is it for? Whatever the functions of sleep are, they probably shift in emphasis across the animal kingdom. There are fundamental differences between rodents and us. On the other hand, even human sleep has some similarities with that of the bee.     

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.     

d-Serine: A key to synaptic plasticity?

Two discoveries have put d-serine in the spotlight of neuroscience. First, d-serine was detected in brain tissue at high levels. Second, it was found to act on the N-methyl-d-aspartate receptor (NMDAR). This receptor is central to use-dependent synaptic plasticity, the cellular process which is widely believed to underlie learning. The ensuing quest for the mechanisms of d-serine synthesis, release and clearance, as well as for its physiological significance has provided a wealth of experimental evidence implicating d-serine in synaptic plasticity. However some key questions remain unanswered. Which cells release d-serine and upon what stimuli? Is d-serine supply dynamically regulated? What is the fate of released d-serine? Answering these questions appears to be an essential step in our understanding of how NMDARs trigger synaptic plasticity and learning. This review will highlight some recent advances and avenues of enquiry in dynamic d-serine signaling in the mammalian brain with emphasis on neurophysiology.     

Stem cell plasticity?

Cells differentiate according to stereotype pedigrees, or at least so we thought. Several studies have challenged this dogma and suggested that stem cells in several tissues may be plastic and switch lineages, but many of the results are open to other interpretations. Is there solid evidence for stem cell plasticity and should we rewrite the textbooks just yet?     

A HAT for sleep?: Epigenetic regulation of sleep by Tip60 in Drosophila

Sleep disturbances are common in neurodegenerative diseases such as Alzheimer disease (AD). Unfortunately, how AD is mechanistically linked with interference of the body’s natural sleep rhythms remains unclear. Our recent findings provide insight into this question by demonstrating that sleep disruption associated with AD is driven by epigenetic changes mediated by the histone acetyltransferase (HAT) Tip60. In this study, we show that Tip60 functionally interacts with the AD associated amyloid precursor protein (APP) to regulate axonal growth of Drosophila small ventrolateral neuronal (sLNv) pacemaker cells, and their production of neuropeptide pigment dispersing factor (PDF) that stabilizes appropriate sleep-wake patterns in the fly. Loss of Tip60 HAT activity under APP neurodegenerative conditions causes decreased PDF production, retraction of the sLNv synaptic arbor required for PDF release and disruption of sleep-wake cycles in these flies. Remarkably, excess Tip60 in conjunction with APP fully rescues these sleep-wake disturbances by inducing overelaboration of the sLNv synaptic terminals and increasing PDF levels, supporting a neuroprotective role for Tip60 in these processes. Our studies highlight the importance of epigenetic based mechanisms underlying sleep disturbances in neurodegenerative diseases like AD.     

Cerebellar Motor Learning: When Is Cortical Plasticity Not Enough?

Classical Marr-Albus theories of cerebellar learning employ only cortical sites of plasticity. However, tests of these theories using adaptive calibration of the vestibulo–ocular reflex (VOR) have indicated plasticity in both cerebellar cortex and the brainstem. To resolve this long-standing conflict, we attempted to identify the computational role of the brainstem site, by using an adaptive filter version of the cerebellar microcircuit to model VOR calibration for changes in the oculomotor plant. With only cortical plasticity, introducing a realistic delay in the retinal-slip error signal of 100 ms prevented learning at frequencies higher than 2.5 Hz, although the VOR itself is accurate up to at least 25 Hz. However, the introduction of an additional brainstem site of plasticity, driven by the correlation between cerebellar and vestibular inputs, overcame the 2.5 Hz limitation and allowed learning of accurate high-frequency gains. This “cortex-first” learning mechanism is consistent with a wide variety of evidence concerning the role of the flocculus in VOR calibration, and complements rather than replaces the previously proposed “brainstem-first” mechanism that operates when ocular tracking mechanisms are effective. These results (i) describe a process whereby information originally learnt in one area of the brain (cerebellar cortex) can be transferred and expressed in another (brainstem), and (ii) indicate for the first time why a brainstem site of plasticity is actually required by Marr-Albus type models when high-frequency gains must be learned in the presence of error delay.     

MS Cortical Lesions on DIR: Not Quite What They Seem?

Objective

Accurate identification and localization of cortical gray matter (CGM) lesions in MS is important when determining their clinical relevance. Double inversion recovery (DIR) scans have been widely used to detect MS CGM lesions. Phase sensitive inversion recovery (PSIR) scans have a higher signal to noise, and can therefore be obtained at a higher resolution within clinically acceptable times. This enables detection of more CGM lesions depicting a clearer cortical and juxtacortical anatomy. In this study, we systematically investigated if the use of high resolution PSIR scans changes the classification of CGM lesions, when compared with standard resolution DIR scans.

Methods

60 patients [30 RR(Relapsing remitting) and 15 each with PP(Primary progressive) and SP(Secondary progressive) MS] were scanned on a 3T Philips Achieva MRI scanner. Images acquired included DIR (1×1×3 mm resolution) and PSIR (0.5×0.5×2 mm). CGM lesions were detected and classified on DIR as intracortical (IC) or leucocortical (LC). We then examined these lesions on corresponding slices of the high resolution PSIR scans and categorized them as IC, LC, Juxtacortical white matter (JC-WM, abutting but not entering cortex) and other white matter (WM, not juxtacortical). Classifications using both scans were noted.

Results

282 IC and 483 LC were identified on DIR. Of the IC lesions, 61% were confirmed as IC on PSIR, 35.5% were reclassified as LC and 3.5% as JC-WM or other WM only. Of the LC DIR lesions, 43.9% were confirmed at LC on PSIR, 16.1% were reclassified as IC and 40% as JC-WM or other WM only. Overall, 50% (381/765) of CGM lesions seen on DIR were reclassified, and 26.5% (203/765) affected WM only.

Conclusions

When compared with higher resolution PSIR, a significant proportion of lesions classified as involving CGM on DIR appear to either contain more white matter than expected or to not involve CGM at all.     

Fluctuations and synchronizations of neural activities during sleep: Neural basis of possible sleep functions?

Physiological and psychological evidence have been accumulated concerning the function of sleep in development and learning/memory. Many conceptual ideas have been proposed to elucidate the mechanisms underlying them. Sleep consists of a wide variety of physiological processes. It has not yet been clarified which processes are involved in development and learning/memory processes. We have found that single neuronal activity exhibits a slowly fluctuating rate of discharge during rapid eye movement (REM) sleep and a random low discharge rate during non-rapid eye movement (NREM) sleep. It is suggested that a structural change of the neural network attractor underlies this neuronal dynamics-alternation by mathematical modeling. Functional interpretation of the neuronal dynamics-alternation was provided in combination with the phase locking of ponto-geniculo-occipital (PGO)/pontine (P) wave to the hippocampal theta wave, each of which is known to be involved in learning/memory processes. More directly, by the long-term sensory deprivation, the dynamics of neural activity during sleep was found to progressively change in a non-monotonic way. This finding reveals a possible interaction between sleep and reorganization of neural network in the matured brain. Here, in addition to the related findings, we described our idea about how sleep contributes to the learning/memory processes and reorganization of neural network of the matured brain through characteristic neural activities during sleep.